Free, convenient returns have become more or less an expectation of the modern retail consumer. Unfortunately, free returns have fueled unprofitable consumer practices such as buying multiple items and sizes, but only keeping favorites or the items that fit. This can prove problematic for retailers, whose already-thin profits are being further squeezed by recent shipping rate hikes by parcel carriers.
This situation may be a challenge, but not an impossible one. By reassessing return policies and/or making smart investments in technology, retailers can weather the increased shipping fees without sacrificing profits or the customer experience.
Retailers should remember that a return policy that was profitable before the rate hikes might not necessarily be as profitable after them. There are a variety of return-policy options for retailers, including:
- Loyalty Club/Fixed Fee Membership Model: Customers pay for an annual membership that lets them make unlimited free returns. Examples of this include Amazon Prime, Lululemon, Barnes & Noble, REI and L.L. Bean (which offers free returns for cardholders). The cost of return shipping is recaptured through memberships, which can increase yearly based on hikes from shipping companies.
- Free Shipping, Paid Returns: With this approach, customers are offered free shipping, but not returns. Instead, the cost of return shipping is deducted from the customer’s refund amount. In addition to helping the retailer offset return costs, this approach can also deter customers from returning items at all.
- Buy Online/Return In Store (BORIS): This method cuts out the cost of return shipping altogether by encouraging consumers to return items in the store. This in turn creates new upsell and cross-sell opportunities for retail store associates.
- Third-party returns management: The newest trend in returns is for retailers to hire a third-party management company. With a third-party management company, consumers bring returns and a receipt to a drop-off location, and an associate handles the return by either traveling to the nearest store and conducting the return themselves, or by shipping the product back and charging either the customer or retailer for the cost, depending on the agreement. This strategy is particularly beneficial for retailers with an e-Commerce-only presence.
Improving Quality Control
Retailers also can try to contain their return expenses by identifying and resolving the root cause of mass-return situations, often caused by quality. Quality issues can cause customers to return purchased items in droves, racking up thousands of dollars in return-shipping fees in a matter of days. Smart technology investments can help retailers identify and resolve such issues early, before the problem spreads and amplifies losses.
For example, a retailer’s prescriptive analytics solution (which analyzes data for anomalies and issues simple, direct prescriptive actions informing employees how to act on insights) alerted its merchandisers that a new summer dress, released only a week prior, was already experiencing above-average rates of return. The solution had analyzed both sales metrics and “unstructured” data like social media comments and online reviews, and found that the reason for most of the returns was due to the product being the “wrong size” — specifically, the product was larger than expected.
The solution sent the retailer’s e-Commerce team a prescriptive action, directing them to change the style’s online product description. The new description informed customers that the size ran large, and that they should purchase one size smaller than usual. This saved the style, and by the end of the season, the dress’ return rate was just 0.76%, which is significantly lower than standard rates.
Personalize Return Policies Based On Profitability
The right analytics solution also can help retailers build a cost-to-serve model, which tailors return policies to reflect customers’ shopping habits. This allows retailers to evaluate specific customers’ behaviors and then tailor return pricing based on how profitable that specific customer is for the retailer.
For example, some retailers offer a set amount customers can spend in order to receive free returns. In this scenario, say a customer who wants to buy a $30 basketball from a sporting goods retailer’s web site realizes he needs to spend $100 dollars to earn free returns. So the shopper also buys a pair of $80 sneakers knowing full well that he plans to return them. This is not a profitable customer on the cost-to-serve model. Solutions like prescriptive analytics can pinpoint specific customers who continually take advantage of the system and offer them an alternate strategy, such as a fixed-fee membership model or a lower returns threshold instead.
When retailers use prescriptive analytics to identify customers who are high-volume returners, a cost-to-serve strategy offering personalized, habit-based returns strategies will ensure profits are maximized on each transaction.
Path To Profits
Given that yearly hikes in shipping are not going away, retailers must continually evaluate how to stay on top of the returns cycle to protect profits. Smart retailers must take advantage of the latest analytics solutions, like prescriptive analytics, to guide strategic decisions that maintain finances without negatively impacting the consumer experience.
As CEO, Guy Yehiav is responsible for overseeing the overall corporate strategy and direction for Profitect. A 25+ year retail supply chain industry veteran, Yehiav has guided the company through multiple concurrent years of significant double-digit growth. Prior to Profitect, Yehiav served as Vice President Sales & Strategy for Oracle’s Value Chain Planning Solutions, where he was responsible for sales, strategy and customer success. He was also founder of Demantra US, a leading global provider of demand-driven planning solutions, which was acquired by Oracle in 2006. Previously, he directed the Global Professional Service Group where he was in charge of creating methodologies and infrastructure through value chain transformations that enabled demand driven and seamless operations for Fortune 1000 companies.